Computer models used in graphics simulations have been used for a range of tasks as diverse as pilot training, automotive design, and architectural walkthroughs. Medical imagery has come to depend on computer model imagery for aiding in diagnoses and for guiding critically dangerous surgeries. The entertainment industry has developed techniques for creating startling special effects and realistic simulations. Even virtual reality games use convincing imagery with great success.
Computer models, however, are still only as good as their definitions. When modeling actual objects, models depend either on incredibly complex written descriptions, on artistically constructed models whose quality depends on the individual skill of a human modeler, or on models derived from scanned or otherwise acquired images. The acquisition of images on which to base model production, even though it includes many forms of acquisition, can be colloquially referred to as scanning.
There are multiple types of scanning. In two-dimensional (2D) scanning, the object of interest is flat and possibly large (e.g., printed documents and whiteboards). When a large object has to be captured at high-resolution, a single image of the object is often insufficient. To ensure capture of the object at sufficient resolution, a camera can be moved in a path in front of the object, or small motions of a camera provide image sampling from slightly different angles. A high-resolution image of the object can then be generated from the sequence of images.
In three-dimensional (3D) scanning, the object of interest has a depth component and it is often necessary to see more than a single side of the object. A camera is moved around the object to get full coverage of the object. The end result is a 3D model of the object, including high-resolution surface textures.
Digital photography allows simple, quick capture of digital images. However, a single image is not good enough to represent 3D artifacts and large 2D surfaces: the back side of a 3D object is not visible in the image, and large 2D objects, such as whiteboards or walls, are not captured with sufficient resolution to be readable.
Document scanning often uses bulky scanners attached to computers with a cumbersome user interface. Some simpler hand-held scanners are appearing, but they must be drawn across the surface of the document, in which case scanning a large board is impractical.
Image/video stitching (mosaicking) methods are known in the art. Typically these are used for scanning an environment, for example a 360-degree panoramic background image. However, image stitching assumes particular camera motions (e.g., a constant center of projection) that are unrealistic for hand-held object scanning, and no guidance exists to aid a user in acquiring the images actually needed to produce a model.
3D scanning is performed with a variety of methods. Very expensive and large laser scanners have been employed to capture the geometric shape of statues. These scanning devices, though, are bulky and require demanding operating environments and on-site calibrations.
Cheaper methods, using uncalibrated cameras, have appeared that simplify the task of 3D object scanning. However, they require significant user training in order to produce a usable image.
What is needed, then, is a method for acquiring images for model production that uses an easily portable camera that does not require extensive calibration prior to each image acquisition. Furthermore, such a method should be able to be performed by a relatively untrained user yet produce images sufficient to produce models that meet measurable desired qualities.